Assessing the hydrogeochemistry and water quality of the Aji-Chay River,northwest of Iran

Aji-Chay River is one of the most important surface reservoirs of northwest of Iran, because it passes through Tabriz city and discharges to Urmia Lake, one of the largest permanent salty lakes in the world. The main objectives of the present study are to evaluate its overall water quality and to explore its hydrogeochemical characteristics, including the potential contamination from heavy metals and metalloids such as Co, Pb, Zn, Cd, Cu, Cr, Al and As. For this purpose, 12 water samples were collected from the main river body and its tributaries within Tabriz plain. The Piper diagram classified water samples mainly into Na–Cl and secondary into Ca–HCO₃ and mixed Ca–Mg–Cl types, denoting a profound salinization effect. The cross-plots showed that natural geochemical processes including dissolution of minerals (e.g., carbonates, evaporites and silicates), as well as ion exchange, are the predominant factors that contribute to fluvial hydrogeochemistry, while anthropogenic activities (industrial and agricultural) impose supplementary effects. Cluster analysis classified samples into two distinct clusters; samples of cluster B appear to have elevated electrical conductivity (EC) values and trace metals concentrations such as Co, Pb and Cd, while SiO₂ and Zn are low in comparison with the samples of the cluster A. The main processes controlling Aji-Chay River hydrogeochemistry and water quality were identified to be salinization and rock weathering. Both are related with geogenic sources which enrich river system with elevated values of Na⁺, Cl^?, Ca²⁺, Mg²⁺, K⁺, SO₄ ^2? and EC as a direct effect of evaporites leaching and elevated values of Pb and Cd as an impact from the weathering process of volcanic formations. According to the US salinity diagram, all of the water samples are unsuitable for irrigation as having moderate to bad quality.     

Assessing the impacts of climate and land use change on streamflow,water quality and suspended sediment in the Kor River Basin,Southwest of Iran

This research addressed the separate and combined impacts of climate and land use change on streamflow, suspended sediment and water quality in the Kor River Basin, Southwest of Iran, using (BASINS–WinHSPF) model. The model was calibrated and validated for hydrology, sediment and water quality for the period 2003–2012. The model was run under two climate changes, two land use changes and four combined change scenarios for near-future period (2020–2049). The results revealed that projected climate change impacts include an increase in streamflow (maximum increases of 52% under RCP 2.6 in December and 170% under RCP 8.5). Projected sediment concentrations under climate change scenarios showed a monthly average decrease of 10%. For land use change scenarios, agricultural development scenario indicated an opposite direction of changes in orthophosphate (increases in all months with an average increase of 6% under agricultural development scenario), leading to the conclusion that land use change is the dominant factor in nutrient concentration changes. Combined impacts results indicated that streamflows in late fall and winter months increased while in summer and early fall decreased. Suspended sediment and orthophosphate concentrations were decreased in all months except for increases in suspended sediment concentrations in September and October and orthophosphate concentrations in late winter and early spring due to the impact of land use change scenarios.     

1990-2016年湘江干流水质变化特征及影响因素分析

基于1990-2016年湘江干流主要断面的水质监测数据,采用综合污染指数法、Spearman秩相关检验和主成分分析法对流域水环境质量演变特征进行综合评价,并结合社会经济指标识别流域主要污染源。综合污染指数结果表明湘江水环境变化趋势明显分为两个阶段,1990-1996年间为水质变好阶段,除个别值外污染指数均小于0.2,1997-2016年间水质呈恶化趋势,水质维持在Ⅲ~IV类之间;Spearman秩相关检验结果表明污染物浓度总体呈增加趋势,其中TP、COD_Mn、Cd、Pb和石油类显著上升;主成分分析结果表明流域污染物主要为NH₄⁺-N、TP和Cd,污染源为生活点源和农业面源,从上游到下游污染程度明显增大,其中湘潭断面水质污染最严重,综合得分为0.9006,道县断面相对较轻,综合得分为-0.7014,城镇化因素是影响流域水环境的主要驱动因素。研究结果可为流域水环境保护和水生态修复提供科学依据。     

Application of multivariate statistical techniques in the assessment of water quality in Sakarya River,Turkey

In this paper, the surface water quality of the Sakarya River in Turkey is assessed by using multivariate statistical techniques. These techniques were applied to the chemical parameters obtained from the five different surface water quality observation stations. Factor and principal component analysis results reveal that the agricultural, anthropogenic and domestic pollution caused differences in terms of water quality. Cluster analysis revealed two different clusters of similarities between the stations, reflecting different chemical properties and pollution levels in the studied river. Surface water quality downstream of the river was different from the water quality upstream. Thus, this study shows the usefulness of multivariate statistical techniques for analysis and interpretation in the surface water quality problem.     

R-mod factor analysis, a popular multivariate statistical technique to evaluate water quality in Khaf-Sangan basin, Mashhad, Northeast of Iran

Water quality data are required in order to compare chemical water analyses and identify water masses. R-mode factor analysis, a popular multivariate statistical tool, has been effectively used for groundwater quality studies. In this paper, the R-mode factor analysis was applied to 50 groundwater samples collected from pumping wells in the Sangan-Khaf basin which is located in the southeast of Mashhad, northeast Iran. The groundwater samples were analysed for chemical parameters. The factor analysis was then performed on the chemical data set. It can be suggested that four factors in R-mode analysis explain more than 94.31% of the total variance. The contribution of each factor at sample points, factor score, was calculated. The spatial distribution of the factor scores for each factor was mapped separately. Since the Sangan iron mine south of the study area probably affects groundwater aquifer, therefore, such studies can be used to manage the groundwater quality in the study area.     

Effects of basin activities and land use on water quality trends in Tahtali Basin, Turkey

Bi-weekly water quality data from seven monitoring stations located within Tahtali Watershed, ?zmir, Turkey and digital land use/land cover data of the same watershed are analyzed in this study. To examine the changes in land use associated with urbanization, the satellite images of the main pool of the Tahtali reservoir prior to filling and subsequent to filling, respectively, are analyzed. Aerial photos of the basin taken in 1995 (October) are compared with images taken in 2005 (November) from the IKONOS satellite through use of several GIS techniques. New residential buildings, greenhouses, and industrial buildings are presented in separate layers, and changes in basin activities are quantified. The effects of urbanization on the water quality are investigated through statistical analysis. The seasonal Kendall test is applied to the water quality parameters monitored bi-weekly at seven stations within the basin for the duration 1997–2005. There was no trend in phosphorus, but there was a negative trend in boron and nitrate and a positive trend in the parameters of biological oxygen demand (BOD) and chemical oxygen demand (COD). The improvement in nitrate concentrations is attributed to the new regulations on the use of fertilizers in greenhouses. However, increase of BOD and COD concentrations is related to the growing settlement areas and industrial zones, which point to the insufficient wastewater treatment within the basin. Soil erosion within the basin is also quantified by the universal soil loss equation using available maps. Estimated total soil loss rate increased about 2.5 times that of 1995 when the changed land use composition in 2005 is considered in the calculations.     

Spatial characterization of water quality in Florida Bay and Whitewater Bay by multivariate analyses: Zones of similar influence

We apply an objective statistical analysis to a 6-yr, multiparameter dataset in an effort to describe the spatial dependence and inherent variation of water quality patterns in the Florida Bay-Whitewater Bay area. Principal component analysis of 16 water quality parameters collected monthly over a 6-yr period resulted in live principal components (PC) that explained 71.8% of the variance of the original variables. The “organic” component (PC₁) was composed of TN, TON, APA, and TOC; the “inorganic N” component (PCII) contained NO₂, NO₃, and NH₄ ⁺, the “phytoplankton” component (PC_III) was made up of turbidity, TP, and Chl a; DO and temperature were inversely related (PC_IV); and salinity was the only parameter included in PC_V. A cluster analysis of mean and SD of PG scores resulted in the spatial aggregation of 50 fixed monitoring stations in Florida Bay and Whitewater Bay into six zones of similar influence (ZSI) defined as Eastern Florida Bay. Core Florida Bay, Western Florida Bay, Coot Bay, the Inner Mangrove Fringe, and the Outer Mangrove Fringe. Marked differences in physical, chemical, and biological characteristics among ZSI were illustrated by this technique. Comparison of medians and variability of parameter values among ZSI allowed large-scale generalizations as to underlying differences in water quality in these regions. For example. Fastern Florida Bay had lower salinity, TON, TOC, TP, and Chl a than the Core Bay as a function of differences in freshwater inputs and water residence time. Comparison of medians and variability within ZSI resulted in new hypotheses as to the processes generating these internal patterns. For example, the Core Bay had very high TON, TOC, and NH₄ ⁺ concentrations but very low NO₃ ^?, leading us to postulate the inhibition of nitrification via CO production by TOC photolysis. We believe that this simple, objective approach to spatial analysis of fixed-station monitoring datasets will aid scientists and managers in the interpretation of factors underlying the observed parameter distribution patterns. We also expect that this approach will be useful in focussing attention on specific spatial areas of concern and in generating new ideas for hypothesis testing.     

Prediction of water quality parameters of Karoon River (Iran) by artificial intelligence-based models

This paper describes the application of multi-layer perceptron (MLP), radial basis network and adaptive neuro-fuzzy inference system (ANFIS) models for computing dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD) levels in the Karoon River (Iran). Nine input water quality variables including EC, PH, Ca, Mg, Na, Turbidity, PO₄, NO₃ and NO₂, which were measured in the river water, were employed for the models. The performance of these models was assessed by the coefficient of determination R ², root mean square error and mean absolute error. The results showed that the computed values of DO, BOD and COD using both the artificial neural network and ANFIS models were in close agreement with their respective measured values in the river water. MLP was also better than other models in predicting water quality variables. Finally, the sensitive analysis was done to determine the relative importance and contribution of the input variables. The results showed that the phosphate was the most effective parameters on DO, BOD and COD.     

Assessment of groundwater quality using multivariate statistical techniques in Hashtgerd Plain, Iran

Multivariate statistical techniques, such as cluster analysis (CA), factor analysis (FA), principal component analysis (PCA), and discriminant analysis (DA), were applied for the evaluation of variations and the interpretation of a large complex groundwater quality data set of the Hashtgerd Plain. In view of this, 13 parameters were measured in groundwater of 26 different wells for two periods. Hierarchical CA grouped the 26 sampling sites into two clusters based on the similarity of groundwater quality characteristics. FA based on PCA, was applied to the data sets of the two different groups obtained from CA, and resulted in three and five effective factors explaining 79.56 and 81.57% of the total variance in groundwater quality data sets of the two clusters, respectively. The main factors obtained from FA indicate that the parameters influencing groundwater quality are mainly related to natural (dissolution of soil and rock), point source (domestic wastewater) and non-point source pollution (agriculture and orchard practices) in the sampling sites of Hashtgerd Plain. DA provided an important data reduction as it uses only three parameters, i.e., electrical conductivity (EC), magnesium (Mg²⁺) and pH, affording more than 98% correct assignations, to discriminate between the two clusters of groundwater wells in the plain. Overall, the results of this study present the effectiveness of the combined use of multivariate statistical techniques for interpretation and reduction of a large data set and for identification of sources for effective groundwater quality management.     

A hydrochemical framework and water quality assessment of river water in the upper reaches of the Huai River Basin, China

This study characterizes the major ion chemistry for river water in the upper reaches of Bengbu Sluice in the Huai River Basin in wet and dry seasons, and assessed the suitability of water quality for irrigation and human consumption. It is found that sodium and calcium are the dominant cations and bicarbonate is the dominant anion in most river water samples. River water in Zhoukou of the Ying River and Bozhou of the Guo River is characterized as a Na–Cl water type, whereas river water from the upper reaches and the lower reaches of the two cities is characterized as a Na-HCO₃ water type, which may be attributed by anthropogenic influences in these cities. The river water types vary from the upstream to the downstream of the Fuyang sluice, which indicates that the sluices play a critical role in determining the water type. The water chemistry of these rivers clearly shows that the second group of rivers is affected more severely by waste effluent than is the first group. Calculated values of sodium adsorption ratio, %Na, and residual sodium carbonate indicate that, in general, most of the river water is of acceptable irrigation quality. The river water in Zhoukou section of the Ying River and the Bozhou section of the Guo River cannot be used as drinking water; pollution control should be further improved and enhanced across the river.     

Evaluation of spatial variations in groundwater quality by WQI and GIS technique: a case study of Virudunagar District, Tamil Nadu, India

Groundwater plays a major life support to mankind. It is the major source to meet the domestic, irrigation and industrial water demands. The depletion of groundwater through excessive consumption and less recharge in the study area has detoriated the quality of groundwater. The present study has analyzed the pre- and post-monsoon physicochemical data of groundwater samples from 49 different bore wells in Virudunagar district. Spatial distribution maps were prepared for various physicochemical parameters using geographic information system. These maps are further classified according to highest desirable, maximum permissible and not permissible prescribed by the World Health Organization. Furthermore, a water quality index (WQI) map was also generated to understand the groundwater quality in the study area. It was observed that the groundwater in the area is hard and alkaline in nature and the WQI reveals that most part of the study area fall under fair water quality class. Also, the effect of recharge during monsoon period has diluted the geochemistry of the groundwater. The application of GIS and WQI in the study area is a promising tool to understand the spatial pattern of groundwater quality and its management.     

Evaluation of spatial and seasonal variations in surface water quality using multivariate statistical techniques

In this study, spatial and seasonal variations of water quality in Haraz River Basin were evaluated using multivariate statistical techniques, such as cluster analysis, principal component analysis and factor analysis. Water quality data collected from 8 sampling stations in river during 4 seasons (Summer and Autumn of 2007, Winter and Spring of 2008) were analyzed for 10 parameters (dissolved oxygen, Fecal Coliform, pH, water temperature, biochemical oxygen demand, nitrate, total phosphate, turbidity, total solid and discharge). Cluster analysis grouped eight sampling stations into three clusters of similar water quality features and thereupon the whole river basin may be categorized into three zones, i.e. low, moderate and high pollution. The principle component analysis/factor analysis assisted to extract and recognize the factors or origins responsible for water quality variations in four seasons of the year. The natural parameters (temperature and discharge), the inorganic parameter (total solid) and the organic nutrients (nitrate) were the most significant parameters contributing to water quality variations for all seasons. Result of principal component analysis and factor analysis evinced that, a parameter that can be significant in contribution to water quality variations in river for one season, may less or not be significant for another one.     

Evaluation of the processes affecting vertical water chemistry in an alluvial aquifer of Mankyeong Watershed, Korea, using multivariate statistical analyses

Vertical variations of redox chemistry and groundwater quality were investigated in an alluvial aquifer beneath an agricultural area, in which deep groundwaters are free of NO₃, Fe, and Mn problems that are frequently encountered during the development of alluvial groundwaters. This study was performed to identify and evaluate vertical chemical processes attenuating these chemical species in the study area. For this study, the processes affecting groundwater chemistry were identified by factor analysis (FA) and the groundwater samples collected from six multilevel samplers were hierarchically classified into three different redox zones by cluster analysis (CA) based on the similarity of geochemical features. FA results indicated three major factors affecting the overall water chemistry: agricultural activities (factor 1), redox reactions (factor 2), and remnant seawater (factor 3). The groundwater quality in the study area was revealed to be controlled by a series of different redox reactions, resulting in different redox zones as a function of depth. It was also revealed that the low Fe and Mn levels in the groundwater of the deeper part are associated with sulfate reduction, which led to precipitation of Fe as iron sulfide and adsorption of Mn on it.     

Ground water quality classification by decision tree method in Ardebil region,Iran

A decision tree-based approach is proposed to predict ground water quality based on the United States Salinity Laboratory (USSL) diagram using the data from aquifers in agricultural lands of Ardebil province, northwest of Iran. Several combinations of hydro chemical parameters of groundwater and monthly precipitation with different lag time were considered to find an accurate and economical alternative for groundwater quality classification. The performance evaluation was based on the number of correctly classified instances (CCI) and kappa statistics. The results suggested the suitability of decision tree-based classification approach for the used data sets. The overall average of CCI and kappa statistic for the prediction of groundwater quality classes based on the USSL diagram was 0.88 and 0.83 %, respectively. Principal component analysis (PCA) was also used to determine the important parameters for groundwater quality classification. The results showed that groundwater quality classification by decision tree is more precise and efficient in comparison with PCA. The best alternative could evaluate groundwater quality class with only two parameters: electrical conductivity and cumulative precipitation of 11 months earlier. The developed model is able to predict water quality class by only two variables and this lead to a reduction in the number of variables analyzed on a routine basis, resulting in a significant reduction in laboratory costs and latency times between the sampling moment and the outcome of the laboratory analyses.     

Evaluation of weir construction on water quality related to algal blooms in the Nakdong River

Understanding the effect of various environmental factors on algal blooms is essential for proper management of water resources. Eight weirs were constructed on the Nakdong River in South Korea between 2010 and 2011 to manage water resources and deal with possible floods and droughts. In this study, water quality observation data were collected from eight representative monitoring sites in the Nakdong River between 2001 and 2016. Particularly, the effect of the weirs construction on water retention time was statistically analyzed in terms of algal growth and other important water quality parameters. While there was slight increase of water temperature (0.8 °C) over 16 years, the concentrations of total phosphorous (TP) and total nitrogen (TN) decreased by 62.3, and 12.9%, respectively, after the construction of weirs. This TP decrease was noticeable, but still high enough to maintain the eutrophic state of the river. Correlation statistical analysis suggests that the Chl-a concentration is positively affected by the changes of TP, TN and chemical oxygen demand. However, there was no direct correlation between Chl-a concentration and the increased water retention time from the weir construction.     

Soil and water pollution derived from anthropogenic activities in the Porsuk River Basin, Turkey

This study aims to investigate the degree of the influence of contaminant sources on both the surface (Porsuk River) and groundwater in the Eskisehir plain, (Turkey) and to determine the changes in groundwater quality after the sewage system was started in 1998. For this purpose surface and groundwater samples were collected from various locations in the Eskisehir plain between May and October, 2001. The Porsuk River is already polluted in the upstream wastewater and by industries such as Nitrogen Fertilizer Factory, Sugar-beet Factory, and Magnesite Factory located around the city of Kutahya. This high-contaminated water forms an eutrophic environment which generates high phosphorus and nitrogen in downstream flow. Agricultural and industrial activities in the Eskisehir plain are an additional source of the pollution of the Porsuk River. The study revealed that some trace elements, Pb, Cr, Mn, Fe, and Cd, are present in high concentrations both in the surface and groundwater besides extremely high quantities of phosphorus, nitrogen and sulfide compounds. In addition, analyses of samples also indicated that there are no considerable contaminations in terms of local pesticides. High concentration of Cd, N and S are found in the groundwater. On the basis of a detailed analysis of the groundwater in the Eskisehir plain, it is concluded that groundwater is not suitable for drinking according to Turkish standards, European Union Standards (EU) and World Health Organization (WHO). An erratum to this article can be found at